Derivation of Atmospheric Aerosol and Cloud Parameters from the Satellite Sensors on Board Himawari 8-9, GCOM-C, Earthcare, and GOSAT2 Satellites
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9-11 Oct. 2013, Melbourne 4th Asia/Oceania Meteorological Satellite Users' Conference Derivation of atmospheric aerosol and cloud parameters from the satellite sensors on board Himawari 8-9, GCOM-C, EarthCARE, and GOSAT2 satellites Teruyuki Nakajima ([email protected]) Surface solar radiation retrieval (1) PV system malfunction detection 2013 result (2011/7 ) EXAM system: Takenaka et al. (JGR 11) (2) Solar car race support DARWIN World Solar Challenge 3,000 km (WSC) in 2011 Tokai U. team Winner 2011-2012 ADELAIDE 2nd in 2013 HIMAWARI7 Next generation satellites AHI specs, JMA/ HIMAWARI-8/9 2016- 16 bands (1km, 2km) EarthCARE Full disk scan every 10min Rapid scan every 2.5 min 2009-, 2016- Aerosol and cloud GOSAT, GOSAT-II 20- monitoring GCOM-C CGOM/C-SGLI 250m, 11ch Current 2nd generation 500m, 2 ch imager 2015- 3rd generation back/forward view 1km, 4 ch Himawari-8&9 with polarization GOSAT2/FTS-SWIR FTS-TIR CAI2 NASA/ LARC Coarse aerosol correction Imaging Dynamics with aerosol ESA-JAXA/EarthCARE Radar Echo Aerosol forcing XCO2, XCH4 Doppler velocity NASA/LARC JMA Advisory Committee for Geostationary Satellite Data Use Members: T. Nakajima (Chair), R. Oki (JAXA), T. Koike, H. Shimoda, T. Takamura, Y. Takayabu, E. Nakakita, T.Y. Nakajima, K. Nakamura, Y. Honda WGs: T.Y. Nakajima (Atmosphere), Y. Honda (Earth surface) Data use exploitation and community supports Data distributions to research community (430GB/day nc) Algorithm developments and requests from foreign agencies and groups? Simulation data (Himawari simulator@JMA, Joint Simulator@JAXA) Foreign agencies JMS JMA ? Meteorological MTSAT research consortium Himawari Advisory committee Universities GCOM-W WG: Atmosphere JAXA GPM w NASA WG: Earth surface EarthCARE w ESA GOSAT MOEJ GOSAT-2 Joint Simulator@JAXA EarthCARE mission NICAM (Non-hydrostatic Icosahedron Atmospheric Model) Module: MIROC, NICAM, NHM, WRF Tropical Cyclone Fengshen simulation 3.5km, 2008/06/21 00Z MTSAT (MRI, Japan; Chiba University, VIS 0.62 μm IR 10.8 μm TB [K] CEReS)+ globally-merged IR (CPC, NOAA) Background: Blue Marble: Next Generation, NASA Observation Simulation Simulation 532 nm backscattering coef. 94 GHz CPR [dBZ] at h=10 km Microwave(19.35GHz) Log10[1/m/str] at h=10 km Simulation Simulation Simulation E Cross section through the TC at Z-Lat plot y longitude = 127°E e , T. Hashino et al. (JGR 13) JMA products for Himawari 8&9 study implement test Category New Product FY2011 FY2012 FY2013 FY2014 FY2015 FY2016 Wind Wind vector N New wind vector Cloud N Standard cloud N High resolution cloud analysis N Improved cloud amount Cloud amount Cloud amount for typhoon analysis Cloud amount in NW Pacific Cloud amount for weather analysis Objective cloud analysis Active cumulus area, cumulonimbus area (MetAir) Wide area cloud analysis TBB Clear sky TBB Land surface Snow ice area Developed with standard cloud Sea surface High resolution SST Sea ice vector Environment N Aerosol (VNIR: yellow sand) N Aerosol (TIR: yellow sand) Volcanic N Aerosol (TIR: volcanic ash Others Low level wind for typhoon analysis Simulation imageries N Instability index Data format Notification Wavelength allocations High resolution NUV (EarthCARE, GCOM-C, GOSAT2) Rich NIR to TIR (Himawari 8&9) vs GOSAT1&2 FTS: time&space sampling Active sensing with lidar and CPR (EarthCARE) Solar P: Polarization F&B: Forward&backward S: Spectrometer Himawari AHI Geo 460 510 650 860 1.61 2.26 3.85 EarthCARE MSI 13:45 670 865 1.65 2.21 Lidar 355P GCOM-C SGLI 10:30 380 412 443 530 674 763 869 1.05 1.38 1.63 2.21 PF PF PB PB GOSAT2 CAI2F 13:00 340F 430 870F 1.6 CAI2B 380B 550B B FTS2 760S 1.6S 2.0S 2.3S Thermal, Microwave Himawari AHI 6.25 7.00 7.35 8.6 9.63 10.5 11.2 12.4 13.3 EarthCARE MSI 8.8 10.8 12.0 CPR 3mm GCOM-C SGLI 10.8 12.0 GOSAT2 CAI2 FTS2 5.5- - - - - - - - -14.3 GOSAT XCO2, XCH4, aerosols June 20, 2013 Sumatra, Indonesia Cloud and Aerosol Imager (CAI) 380, 670, 860, 1600nm FOV 500m 750m Push-broom imager, Cheap! Four channel aerosol species: Higurashi and Nakajima (GRL 02) Use of TIR spectrum for coarse particles Dust events Coarse aerosol correction for CO2 retrieval from GOSAT 1&2 (planned) AIRS IR AOT (May 11, 2011) Dust Height (Apr. 23, 2009 1830 UTC) Courtesy: Hyojin Han & B.J. Sohn (2013) AOTcoarse Heightcoarse AOTfine <<1 in TIR Dust optical properties (multi-time/pixel method) Neutral reflectance method (Kaufman, JGR 87) Extended for any AOT (Yoshida et al., ACP 13) Africa MODIS band 9 (443nm) 9 year mean (2003-2011), OMI prescreen Lower SSA in Asia: Dust and soot mixed 0.95 SSA related with land albedo Asia SSA 0.90 0.85 3 2 AOT 1 0 Yoshida & Murakami (AO 08) Yoshida et al. (ACPD 12) RE>0 RE=0 RE<0 Google earth FIRE campaign (July 7, Cloud observables North America 1987 Off California COT-RE diagram: Nakajima and King wind (JAS 90), TY. Nakajima & Nakajima m] (JAS95) µ CFODD: TY. Nakajima et al. (JAS10) RE [ RE [µm] (iii) (iv) COT RE JMA/NHM+UT/ACBM (2D-bin model): (i) (ii) K. Suzuki. (JAS10); Y. Sato (JAS11, 12) (Suzuki et al. 2010a) RE=5-10µm 10-15µm 15-20µm Bin-model simulation COT (z) τ Optical Depth CPR Radar Reflectivity [dBZ] Cloudsat Aerosol & Cloud detection capability Geos for good aerosol and cloud variation and motion Geos for bridging EarthCARE, GCOM-C, GOSAT2 observation EarthCARE profiling for Geos analysis GOSAT column trace gases (CO2, CO, CH4) and aerosols Himawari EarthCARE GCOM-C GOSAT2 Time variation, motion OK - - - AOT&AE dark target OK OK OK OK Aerosol species dark target medium - OK OK AOT over bright land medium - OK OK Coarse particle AOT OK - OK OK SSA neutral reflectance medium - OK OK Aerosol profiling (nadir) - Lidar - O2A Screen by cloud shadow - - UV UV COT OK OK OK OK RE 1.6, 2.2, 3.7 1.6, 2.2 1.6, 2.2 1.6, 2.2(FTS) Clouds over snow OK OK OK OK Thin cirrus OK medium OK FTS Cloud profiling (nadir) - CPR - - PREDE skyradiometer sites (SKYNET) AOT comparison • Unique on-site calibration system with AERONET • AOT, SSA, SZF, COT, RE, O3, WV • Approval process for GAW contributing network • Co-location with ADNET lidar 99 sites Conclusions JMA preparation for Himawari 8&9 processing started with healthy collaboration with the research community. 2017 era: Himawari 8&9, EarthCARE, GCOM-C, and GOSAT-2 High resolution NUV data sets for aerosol detection COT-RE, CFODD for cloud process analysis with active sensing combined with imagers SKYNET skyradiometer network expanding CEOS and WMO should enhance the international satellite program coordination • Japan Basic plan for space policy (Cabinet Office, Government of Japan) endangers JAXA earth observation Himawari 8&9 data distribution to research community (Planned) JMA satellite center DIAS@GEOSS Institute NICT@WDS Universities Radiometer data file data (permanent archive) server Researcher Resampling (e.g. SINET (geometric., University etc) semi-realtime radiometric, grid (best effort) trans.) data Research networks server Researcher Himawari Cloud standard data Organization... FY2014 data 430GB/day (non compressed) server 160TB/year (nc) Foreign Research Researcher networks Volume netCDF reduction (low (eg. APAN, AARNet, resolution) (regional obs.) Intemet 2) 200GB/day (nc) Meteorological service center HRIT data realtime Operational Data files (TBD) server private lines Volume similar to current Meteorologica MTSAT (11GB/day, nc) l enterprises.